147 related articles for article (PubMed ID: 24267147)
1. Evaluating a linear k-mer model for protein-DNA interactions using high-throughput SELEX data.
Kähärä J; Lähdesmäki H
BMC Bioinformatics; 2013; 14 Suppl 10(Suppl 10):S2. PubMed ID: 24267147
[TBL] [Abstract][Full Text] [Related]
2. Transcription factor-binding k-mer analysis clarifies the cell type dependency of binding specificities and cis-regulatory SNPs in humans.
Tahara S; Tsuchiya T; Matsumoto H; Ozaki H
BMC Genomics; 2023 Oct; 24(1):597. PubMed ID: 37805453
[TBL] [Abstract][Full Text] [Related]
3. A comparative analysis of transcription factor binding models learned from PBM, HT-SELEX and ChIP data.
Orenstein Y; Shamir R
Nucleic Acids Res; 2014 Apr; 42(8):e63. PubMed ID: 24500199
[TBL] [Abstract][Full Text] [Related]
4. Quantitative modeling of transcription factor binding specificities using DNA shape.
Zhou T; Shen N; Yang L; Abe N; Horton J; Mann RS; Bussemaker HJ; Gordân R; Rohs R
Proc Natl Acad Sci U S A; 2015 Apr; 112(15):4654-9. PubMed ID: 25775564
[TBL] [Abstract][Full Text] [Related]
5. BEESEM: estimation of binding energy models using HT-SELEX data.
Ruan S; Swamidass SJ; Stormo GD
Bioinformatics; 2017 Aug; 33(15):2288-2295. PubMed ID: 28379348
[TBL] [Abstract][Full Text] [Related]
6. A novel
Guo Y; Tian K; Zeng H; Guo X; Gifford DK
Genome Res; 2018 Jun; 28(6):891-900. PubMed ID: 29654070
[TBL] [Abstract][Full Text] [Related]
7. Comparative analysis of models in predicting the effects of SNPs on TF-DNA binding using large-scale in vitro and in vivo data.
Han D; Li Y; Wang L; Liang X; Miao Y; Li W; Wang S; Wang Z
Brief Bioinform; 2024 Jan; 25(2):. PubMed ID: 38517697
[TBL] [Abstract][Full Text] [Related]
8. Better estimation of protein-DNA interaction parameters improve prediction of functional sites.
Nagaraj VH; O'Flanagan RA; Sengupta AM
BMC Biotechnol; 2008 Dec; 8():94. PubMed ID: 19105805
[TBL] [Abstract][Full Text] [Related]
9. SELEX-Seq: A Method to Determine DNA Binding Specificities of Plant Transcription Factors.
Smaczniak C; Angenent GC; Kaufmann K
Methods Mol Biol; 2017; 1629():67-82. PubMed ID: 28623580
[TBL] [Abstract][Full Text] [Related]
10. Statistics of protein-DNA binding and the total number of binding sites for a transcription factor in the mammalian genome.
Kuznetsov VA; Singh O; Jenjaroenpun P
BMC Genomics; 2010 Feb; 11 Suppl 1(Suppl 1):S12. PubMed ID: 20158869
[TBL] [Abstract][Full Text] [Related]
11. In vitro DNA-binding profile of transcription factors: methods and new insights.
Wang J; Lu J; Gu G; Liu Y
J Endocrinol; 2011 Jul; 210(1):15-27. PubMed ID: 21389103
[TBL] [Abstract][Full Text] [Related]
12. A highly efficient and effective motif discovery method for ChIP-seq/ChIP-chip data using positional information.
Ma X; Kulkarni A; Zhang Z; Xuan Z; Serfling R; Zhang MQ
Nucleic Acids Res; 2012 Apr; 40(7):e50. PubMed ID: 22228832
[TBL] [Abstract][Full Text] [Related]
13. High-Throughput Protein Production Combined with High- Throughput SELEX Identifies an Extensive Atlas of Ciona robusta Transcription Factor DNA-Binding Specificities.
Nitta KR; Vincentelli R; Jacox E; Cimino A; Ohtsuka Y; Sobral D; Satou Y; Cambillau C; Lemaire P
Methods Mol Biol; 2019; 2025():487-517. PubMed ID: 31267468
[TBL] [Abstract][Full Text] [Related]
14. DNA sequence+shape kernel enables alignment-free modeling of transcription factor binding.
Ma W; Yang L; Rohs R; Noble WS
Bioinformatics; 2017 Oct; 33(19):3003-3010. PubMed ID: 28541376
[TBL] [Abstract][Full Text] [Related]
15. A novel approach for transcription factor analysis using SELEX with high-throughput sequencing (TFAST).
Reiss DJ; Howard FM; Mobley HL
PLoS One; 2012; 7(8):e42761. PubMed ID: 22956994
[TBL] [Abstract][Full Text] [Related]
16. A map of direct TF-DNA interactions in the human genome.
Gheorghe M; Sandve GK; Khan A; Chèneby J; Ballester B; Mathelier A
Nucleic Acids Res; 2019 Feb; 47(4):e21. PubMed ID: 30517703
[TBL] [Abstract][Full Text] [Related]
17. BinDNase: a discriminatory approach for transcription factor binding prediction using DNase I hypersensitivity data.
Kähärä J; Lähdesmäki H
Bioinformatics; 2015 Sep; 31(17):2852-9. PubMed ID: 25957350
[TBL] [Abstract][Full Text] [Related]
18. Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study.
Ambrosini G; Vorontsov I; Penzar D; Groux R; Fornes O; Nikolaeva DD; Ballester B; Grau J; Grosse I; Makeev V; Kulakovskiy I; Bucher P
Genome Biol; 2020 May; 21(1):114. PubMed ID: 32393327
[TBL] [Abstract][Full Text] [Related]
19. TherMos: Estimating protein-DNA binding energies from in vivo binding profiles.
Sun W; Hu X; Lim MH; Ng CK; Choo SH; Castro DS; Drechsel D; Guillemot F; Kolatkar PR; Jauch R; Prabhakar S
Nucleic Acids Res; 2013 Jun; 41(11):5555-68. PubMed ID: 23595148
[TBL] [Abstract][Full Text] [Related]
20. DeepD2V: A Novel Deep Learning-Based Framework for Predicting Transcription Factor Binding Sites from Combined DNA Sequence.
Deng L; Wu H; Liu X; Liu H
Int J Mol Sci; 2021 May; 22(11):. PubMed ID: 34073774
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
